How to integrate Etermin MCP with LangChain

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Introduction

This guide walks you through connecting Etermin to LangChain using the Composio tool router. By the end, you'll have a working Etermin agent that can add new client contact for booking, remove canceled appointment from calendar, create voucher for returning customer, delete outdated service from offerings through natural language commands.

This guide will help you understand how to give your LangChain agent real control over a Etermin account through Composio's Etermin MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Connect your Etermin project to Composio
  • Create a Tool Router MCP session for Etermin
  • Initialize an MCP client and retrieve Etermin tools
  • Build a LangChain agent that can interact with Etermin
  • Set up an interactive chat interface for testing

What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.

Key features include:

  • Agent Framework: Build agents that can use tools and make decisions
  • MCP Integration: Connect to external services through Model Context Protocol adapters
  • Memory Management: Maintain conversation history across interactions
  • Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

What is the Etermin MCP server, and what's possible with it?

The Etermin MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Etermin account. It provides structured and secure access to your appointment scheduling system, so your agent can perform actions like creating contacts, managing bookings, updating resources, and handling calendar events on your behalf.

  • Automated contact and user creation: Instantly add new clients or team members to your Etermin account, streamlining onboarding and customer management.
  • Effortless appointment and calendar management: Let your agent delete existing appointments or calendars, freeing up schedules and reducing manual work.
  • Resource and service administration: Automatically create or remove resources and services, ensuring your booking system stays current as your business evolves.
  • Voucher and webhook setup: Quickly generate new vouchers for promotions or set up webhooks for real-time event notifications and integrations.
  • Contact and service deletion: Easily remove outdated contacts or services, keeping your scheduling platform organized and clutter-free.

Supported Tools & Triggers

Tools
Create ContactTool to create a new contact in eTermin.
Create eTermin ResourceTool to create a new resource.
Create UserTool to create a new user.
Create VoucherTool to create a new voucher in eTermin.
Create WebhookTool to create a new webhook in eTermin.
Delete AppointmentTool to delete an appointment.
Delete calendarTool to delete a calendar.
Delete ContactTool to delete a contact.
Delete ResourceTool to delete an existing resource.
Delete ServiceTool to delete a service.
Delete UserTool to delete a user.
Delete VoucherTool to delete an existing voucher.
Delete WebhookTool to delete an existing webhook.
Get AppointmentsTool to retrieve a list of appointments.
Get CalendarsTool to retrieve calendars.
Get ContactsTool to retrieve a list of contacts.
Get ResourcesTool to retrieve all resources.
Get ServicesTool to retrieve a list of services.
Get UsersTool to retrieve a list of users.
Get Working TimesTool to retrieve working times for a specific calendar.
List VouchersTool to list vouchers.
List WebhooksTool to retrieve webhooks.
Update calendarTool to update an existing calendar.
Update ContactTool to update an existing contact in eTermin.
Update ResourceTool to update an existing resource.
Update ServiceTool to update an existing service.
Update VoucherTool to update an existing voucher.
Update WebhookTool to update an existing webhook.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

Before starting this tutorial, make sure you have:
  • Python 3.10 or higher installed on your system
  • A Composio account with an API key
  • An OpenAI API key
  • Basic familiarity with Python and async programming

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.

Install dependencies

pip install composio-langchain langchain-mcp-adapters langchain python-dotenv

Install the required packages for LangChain with MCP support.

What's happening:

  • composio-langchain provides Composio integration for LangChain
  • langchain-mcp-adapters enables MCP client connections
  • langchain is the core agent framework
  • python-dotenv loads environment variables

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your requests to Composio's API
  • COMPOSIO_USER_ID identifies the user for session management
  • OPENAI_API_KEY enables access to OpenAI's language models

Import dependencies

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with Etermin functionality through MCP

Initialize Composio client

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
What's happening:
  • We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
  • Creating a Composio instance that will manage our connection to Etermin tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

# Create Tool Router session for Etermin
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['etermin']
)

url = session.mcp.url
What's happening:
  • We're creating a Tool Router session that gives your agent access to Etermin tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use
  • This approach allows the agent to dynamically load and use Etermin tools as needed

Configure the agent with the MCP URL

client = MultiServerMCPClient({
    "etermin-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("gpt-5", tools)
What's happening:
  • We're creating a MultiServerMCPClient that connects to our Etermin MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • get_tools() retrieves all available Etermin tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model

Set up interactive chat interface

conversation_history = []

print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Etermin related question or task to the agent.\n")

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ['exit', 'quit', 'bye']:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
What's happening:
  • We initialize an empty conversation_history list to maintain context across interactions
  • A while loop continuously accepts user input from the command line
  • When a user types a message, it's added to the conversation history and sent to the agent
  • The agent processes the request using the ainvoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully

Run the application

if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • We call the main() function using asyncio.run() to start the application

Complete Code

Here's the complete code to get you started with Etermin and LangChain:

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['etermin']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "etermin-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Ask any Etermin related question or task to the agent.\n")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You've successfully built a LangChain agent that can interact with Etermin through Composio's Tool Router.

Key features of this implementation:

  • Dynamic tool loading through Composio's Tool Router
  • Conversation history maintenance for context-aware responses
  • Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.

How to build Etermin MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Etermin MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Etermin MCP with Claude Agent SDK

Google ADK

Google ADK

Use Etermin MCP with Google ADK

Vercel AI SDK

Vercel AI SDK

Use Etermin MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Etermin MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Etermin MCP with LlamaIndex

CrewAI

CrewAI

Use Etermin MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Etermin MCP?

With a standalone Etermin MCP server, the agents and LLMs can only access a fixed set of Etermin tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Etermin and many other apps based on the task at hand, all through a single MCP endpoint.

Can I use Tool Router MCP with LangChain?

Yes, you can. LangChain fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Etermin tools.

Can I manage the permissions and scopes for Etermin while using Tool Router?

Yes, absolutely. You can configure which Etermin scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Etermin data and credentials are handled as safely as possible.

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